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Background: Clinical reasoning is a professional capability required for clinical practice. In preclinical training, clinical reasoning is often taught implicitly, and feedback is focused on discrete outcomes of decision-making. This makes it challenging to provide meaningful feedback on the often-hidden metacognitive process of reasoning to address specific clinical reasoning difficulties. Therefore, we designed the Clinical Diagnosis Assessment, an assessment for learning, to explicitly train Type 1 and Type 2 reasoning skills in optometry students. Decision justification was included to prompt reflective practice and expose metacognitive reasoning. By manipulating assessment task features, we aimed to broaden students' experience with clinical reasoning strategies and identify specific clinical reasoning challenges. Methods: The Clinical Diagnosis Assessment was designed with two parts; to explicitly train Type 1 and Type 2 clinical reasoning strategies respectively. A validated clinical reasoning measure, the Diagnostic Thinking Inventory for Optometry was used to measure change in clinical reasoning skill. Clinical Diagnosis Assessment and Diagnostic Thinking Inventory scores were quantitatively compared against written exams and OSCEs. Focus groups explored student perception and approach to the assessment. Results: Out of a total of 67 second-year Optometry students, 55 students (82%) completed the Diagnostic Thinking Inventory for Optometry, 50 students (75%) consented to use of assessment scores and 17 students (26%) participated in focus groups. Quantitative analysis indicated modest but significant Pearson coefficients of determination between Clinical Diagnosis Assessment and OSCE performance (p <.05, r2 = 0.106), and examination outcomes (p <.01, r2 = 0.184). Diagnostic Thinking Inventory scores increased after studying for the Clinical Diagnosis Assessment (p <.01). Four themes were identified through qualitative analysis: an authentic task prompting development of key skills required for the workplace; execution of CR strategies; exposing CR difficulties; and motivation to seek holistic feedback to improve future practice. Conclusions: The assessment exposed students underlying thinking, allowing identification of a range of clinical reasoning difficulties such as semantic transformation, prioritization, management planning, cognitive bias and managing diagnostic uncertainty. Better understanding of clinical reasoning difficulties will allow targeted remediation and inform curriculum design. The Clinical Diagnosis Assessment improves clinical reasoning skill, while promoting execution and awareness of discreet clinical reasoning strategies. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to determine the feasibility of using readily accessible technology, anterior segment optical coherence tomography (AS‐OCT), to detect and grade meibomian gland dropout and examine its interchangeability with the Oculus Keratograph 5M (K5M). Methods: A total of 30 participants (30 eyes) with a median age of 21 (range = 19–28 years) were recruited. Meibography was performed using two commercially available imaging devices to look at the structure of the meibomian glands and grade them subjectively in real time, and image analysis was used to quantify meibomian gland loss objectively. Gland loss as imaged by the two techniques was graded using the meiboscore grading schema. Test–retest reliability was determined with intraclass correlation coefficients (ICCs). Weighted kappa was used to evaluate agreement between the two imaging devices and four methods of image analysis. Spearman and Pearson correlation coefficients were used to determine the association of structural measurements between each of the techniques. The agreement between the two imaging techniques was determined with the Bland–Altman analysis. Results: Reliability of subjective grading was strong for AS‐OCT (ICC: 0.92, 95% CI: 0.83–0.96, p < 0.001) and K5M (ICC: 0.96, 95% CI: 0.96–0.91, p = 0.001). Image analysis with ImageJ reliability was strong between the imaging devices (ICC: 0.84, 95% CI: 0.55–0.94, p < 0.001). Agreement between each subjective technique was fair, κ = 0.45 (95% CI: 0.17–0.73, p < 0.001) and a positive Spearman correlation was also observed (r = 0.52, p < 0.001). There was no significant difference between the mean meibomian gland loss measured with ImageJ between AS‐OCT and K5M (0.92 ± 6.28, p = 0.26). The 95% limits of agreement were −12.45% to +14.04%. Conclusion: These findings suggest subjective real‐time grading of meibomian gland loss could be performed using readily available AS‐OCT technology and that this method was interchangeable with the K5M. [ABSTRACT FROM AUTHOR]